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-developing a hybrid machine learning/process-based model of anaerobic digestion processes Performing techno-economic and lifecycle analysis of microgrids build around novel biogas-fueled generation
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, mathematics, physics, or a related field. The ideal candidate should demonstrate a record of publications in the area. Strong knowledge in machine learning, statistics and programming skills (R, Python
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-inflammatory response. This molecular process plays a significant role in various acute and chronic inflammatory disorders including acute Graft versus Host Disease (GVHD), a common and severe complication
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, candidates should exhibit a strong background in quantitative fields such as Mathematics, Physics, Engineering, or Computer Science. This position promises a vibrant and cooperative atmosphere within
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apply cutting-edge deep learning models, including LLMs, to process and analyze large-scale EMR datasets. Design predictive models to assess disease trajectories, treatment outcomes, and patient risk
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strong quantitative background, with a PhD in computational biology, bioinformatics or related field including bioengineering, computer science, statistics, mathematics, electrical engineering, physics
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of the selected candidate, budget availability, and internal equity. Pay Range: $72,000-$82,000 The Rock Physics and Geomaterials Laboratory (link is external) at Stanford University invites applications for three
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to include (among other things) diversity of genders, races and ethnicities, cultures, physical and learning differences, sexual orientations and identities, veteran status, and work and life experiences
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-author manuscript with related analysis code and references later during the recruitment process. Stanford is an equal opportunity employer and all qualified applicants will receive consideration without
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the application process, submission of materials, or the program, please inquire with Robyn Foote, rfoote@stanford.edu (link sends e-mail) . Required Qualifications: The applicant must be enrolled in an ACGME